An Efficient Fusion Algorithm on Conflicting Evidence

被引:2
作者
Yang, Jinyuan [1 ]
Huang, Xinhan [1 ]
Wang, Min [1 ]
机构
[1] Huazhong Univ Sci & Technol, Dept Control Sci & Engn, Wuhan 430074, Peoples R China
来源
PROCEEDINGS OF THE 8TH IEEE/ACIS INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION SCIENCE | 2009年
关键词
conflict evidence; information fusion; DST; DSmT;
D O I
10.1109/ICIS.2009.118
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
DSmT would resolve the issue of evidence portfolios when the high conflict of evidences appeared. But the computation oversized more easily because more focus elements were additional in the DSmT rules. And the fusion result was worse than that of DST when the low conflict situation was occurred. In order to efficiently combine high conflicting evidences, an improved fusion algorithm on conflict evidence is proposed. The method uses conflict mass as a basis for judgment in conflict situations. DST rules are adopted when conflict mass is lower. And DSmT fusion algorithm was adopted while opposition. During the switch between DST and DSmT, a mutual belief degree and support degree of the evidence is calculated firstly. Then the weight is obtained. Finally the conflict mass redistributed to every focus element weightily. Compared with the exist methods, this new algorithm has the advantage of better performance and more rational.
引用
收藏
页码:650 / 654
页数:5
相关论文
共 50 条
  • [31] FAST EVIDENCE-BASED INFORMATION FUSION
    Moenks, Uwe
    Lohweg, Volker
    [J]. 2014 4TH INTERNATIONAL WORKSHOP ON COGNITIVE INFORMATION PROCESSING (CIP), 2014,
  • [32] Multi-Sensor Fusion Method Based on Checking Unscented Information Fusion Algorithm
    Liu Z.
    Zhang G.
    Zheng Y.
    He X.
    [J]. Qiche Gongcheng/Automotive Engineering, 2020, 42 (07): : 854 - 859
  • [33] An Information Fusion Algorithm for Multiple GPS Track Data
    Chen, Dewang
    Cai, Baigen
    Tang, Tao
    [J]. ICNC 2008: FOURTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 6, PROCEEDINGS, 2008, : 468 - 472
  • [34] A multi-MEMS sensors information fusion algorithm
    Shi Jingwei
    Zhou Yongjie
    Zhang Haiyun
    Zhang Tao
    Wang Leigang
    Ren Wei
    Luan Mengkai
    Liu Huifeng
    [J]. 26TH CHINESE CONTROL AND DECISION CONFERENCE (2014 CCDC), 2014, : 4675 - 4680
  • [35] Kalman Smoother and Weighted Fusion Algorithm for Fractional Systems
    Sun, Xiaojun
    Yan, Guangming
    Zhang, Bo
    [J]. PROCEEDINGS OF 2013 2ND INTERNATIONAL CONFERENCE ON MEASUREMENT, INFORMATION AND CONTROL (ICMIC 2013), VOLS 1 & 2, 2013, : 151 - 158
  • [36] Information Fusion Algorithm for Target Tracking of Composite Seeker
    Han, Yumeng
    Jia, Xiaohong
    [J]. 2016 IEEE INTERNATIONAL CONFERENCE ON ELECTRONIC INFORMATION AND COMMUNICATION TECHNOLOGY ICEICT 2016 PROCEEDINGS, 2016, : 411 - 415
  • [37] Spacial Gyroscope Calibration Algorithm Base on Fusion Filter
    Xu Fan
    You Taihua
    Guo Kang
    [J]. AOPC 2017: SPACE OPTICS AND EARTH IMAGING AND SPACE NAVIGATION, 2017, 10463
  • [38] Image fusion with the hybrid evolutionary algorithm and response analysis
    Maslov, IV
    [J]. MULTISENSOR, MULTISOURCE INFORMATION FUSION: ARCHITECTURES, ALGORITHMS AND APPLICATIONS 2005, 2005, 5813 : 25 - 33
  • [39] Multi-sensor fusion: an Evolutionary algorithm approach
    Maslov, Igor V.
    Gertner, Izidor
    [J]. INFORMATION FUSION, 2006, 7 (03) : 304 - 330
  • [40] An improved bayes fusion algorithm with the parzen window method
    Wang, G
    Zhang, DG
    Zhao, H
    [J]. PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON INFORMATION FUSION, VOL I, 2002, : 651 - 657